TRowePrice

• Actively managed funds are dying out compared to passive funds (Bogle)
• Larry Puglia has managed to outperform:
  • In recent years not as much.
  • Fund is now 30 billion dollars
    • What happens when you get so large?
    • Why did he get so large?
  • Passive seemed to win over active, why?

• How should we allocate resources (i.e. asset classes)?
• How should we 'pick' investments?
  1. Macro Projection (ECON 202, ECON 225)
  2. Filtering (Logic, Basic Finance)
  3. Analysis (Financial Stmt Analysis)
  4. Selection (Logic, Judgment)
  5. Portfolio Optimization (Portfolio Analysis)
  6. Hedging (Derivatives/ International Finance)

We can use some detailed forecasting, but this is better left to the macro-economist. That is after all… what they get paid to do. So let's not re-work their jobs, instead use (i.e. read) what they produce.

1. International Monetary Fund (IMF)
2. OECD (Organisation for Economic Co-operation and Development)
3. World Bank
4. The Federal Reserve (Mostly US)

Each year the IMF produces the World Economic Outlook report.

• You can read the full report with all of its little insights and see what the staff economists at the world bank are foreseeing.
• You can also just download the data and play with it.

As with most macro-economic reports we are focused on economic activity. That can be interpreted through estimations of GDP growth, inflation and 'economic indicators'. Note that 'output' means GDP.

The OECD provides a wealth of economic forecasts and data as well as charts you can sort and play around with. With very little work you can gain an understanding of what is going on globally.

• I suggest playing around on their website.
• You can also go to their data page and search for information that is relevant.

Similar to the above two, the World Bank and Federal Reserve have a wealth of information on their sites:

• You likely know about the St. Louis Federal Reserve's website FRED.
• The World Bank also provides similar information on a global scale.

Again, here we are attempting to just determine what are the global directions things are headed. Global macro-economics are extremely complex (and integrated) and so forecasting is itself extremely difficult to pull off with any level of accuracy. Best to leave it to the pros on this one.

You've just completed your global macro-economic trends analysis. You have a firm grasp of where things are headed.

1. China is still growing and is the dominant economic region for the next few years.
2. Advanced Economies (America included) are growing but slowly (2-4% p.a.).
3. Emerging Markets may out pace advanced economies, but are risky.

The next step is to select sectors that are expected to out-perform within each country. For this discussion we should be looking at China (i.e. invest where the growth is). But since much of that information is not in English, we will use America. Application is the same.

The next question becomes which sectors should we invest in?

• Some sectors are 'counter cyclical' (gold miners).
• Some are 'dead' for a given economy (textile manufacturing in England).
• Some are growing (tech…everywhere).
• Some are in decline (traditional car manufacturing v. EV).

Q: How to know?

A: Plot long-run sector fund returns (sector ETFs) and see what is going on.

At the time of this writing, we can see a few sectors that stick out even if we change the time window:

1. Internet (FDN) / Software (IGV)
2. Semi-Conductors (SMH)
3. Clean Energy (PBW, recently)
4. Technology (XLK)
5. Bio-Technology (IBB)

Many of these have even significantly outperformed the SPY in recent years. These sectors are growing, we should allocate more of our portfolio to stocks which exist within these sectors (or buy the ETFs themselves).

After determining what sectors you want to be invested in (and what country), you can screen for stocks on some basic knock out conditions from simple finance:

1. They have too much debt compared to income.
2. They are not profitable (careful, this eliminates start-ups).
3. They are nearing bankruptcy (Altman-Z score).
4. Their Earnings are not growing on a per share basis (EPS growth).

Clearing out the bad firms–you are left with firms to investigate.

An easy screener to use is Yahoo Finance's screener, but you can use Bloomberg, Reuters, Koyfin, etc.

As the case discusses, there are two types of financial analysis one may use in choosing to invest in a particular firm:

1. Technical Analysis - This approach involved the identification of profitable investment opportunities based on trends in stock prices, volume, market sentiment, and the like.
2. Fundamental Analysis - This approach relied on insights afforded by an analysis of the economic fundamentals of a company and its industry: supply and demand, costs, growth prospects, and the like. (Source: Cases in Finance, Larry Puglia and TRowePrice.)

Technical Analysis is often called 'charting'. The technique does take some practice and it is often wrong.

• It is very difficult to say what is the best line, or even where to start your lines and end them.
• In theory, TA works because everyone else should be coming to the same conclusions. If markets are efficient, then trends (that everyone else is following), should play out and you can predict them.
  • The reality is… given the first item, it's hard to determine what trends everyone else is seeing.
  • How do you know the line(s) you draw are the same as everyone else? If the lines are off, will everyone trade on the same 'signal'?

• Technical indicators are often suggested to 'fix' this hand drawn issue.
  • Exponential Moving Average (EMA), Simple Moving Average (SMA), Relative Strength Index (RSI), Commodity Channel Index (CCI), Parabolic SAR (pSAR), Moving Average Convergence Divergence (MACD), etc.
  • What days do you use for the average? There is a lot of debate on which ones work. If there is no standard consensus, then (under EMH) there is no market herding–i.e. no trend.
  • Worse still, what frequency? 1m, 5m, 1h, 1D, 1M, 1Y … decades?

Fundamental Analysis falls into two major categories:

1. Discounted Cash Flows – Collecting, Projecting and Analyzing a firm's cash flows (FCF). Discounting them backwards gets the value of the firm. (We practiced this last week.)
2. Comparables – Rather than using cash flows (which can be messy), compare your firm against other firms with basic financial ratios. (These are also called 'comps')

\[ FCF = EBIT(1-t)+D\&A - CAPEX - \Delta NOWC \]

or

\[ FCF = NOPAT - \Delta PP\&E - \Delta NOWC \]

Discounting given a risk-rate gets you the firm's value:

\[ V_{firm} = \frac{FCF_1}{(1+r)^{1}}+\frac{FCF_2}{(1+r)^{2}}+\dots+\frac{FCF_n+Terminal}{(1+r)^{n}} \]

Note: \( V_{firm} \) is nearly identical to NPV. (This is important.)

Once you have found the firm's value you can find its intrinsic price/value per share:

\[ P_v = \frac{V_{firm}}{shares\ outstanding} \]

\( P_v \geq P_m \), value is higher than price in the market, buy the asset.

\( P_v < P_m \), value is lower than price in the market, do not buy (sell).

(Hint: rules are the same as NPV.)

Download or use full screen at the bottom right.

Comparables assume that markets are efficient (EMH). If markets are efficient, then the value of one firm is equivalent in proportion to other firms.

• Sometimes comparables are extremely useful. If a firm does not have market data, you cannot usually find an appropriate discount rate (\( r \)) from which to do DCF.
• However, as noted above–you cannot usually find mis-pricing using comparables, for comparables to work, you have to assume that market prices are correct!
  • If market prices are correct (all the time), markets are efficient, therefore you should not be picking stocks as an active manager. Instead, be a passive investor.

Some of the most common comparables (valuation metrics) are:

• \( \frac{Enterprise\ Value}{Sales} \), EV/S
• \( \frac{P}{E} \), PE Ratio
• \( \frac{P}{Book} \), Price to Book Ratio
• \( \frac{P}{Sales} \), Price to Sales Ratio
• \( \frac{P}{FCF/S} \), Price to Cash Flow per Share Ratio

To do a comparables analysis, you need to identify other 'like' firms to the one you are attempting to value. For example, suppose we were attempting to value Kroger (KR).

Having collected these comparables we find the average of the metrics, and using Kroger's data we can back out what the price of the stock should be. For example we know that the average Forward P/E was 29.36, so we can estimate Kroger's price using their EPS of $3.74 to be:

\[ P/E_{Comp} \times Earnings_{Kroger} = Price_{Kroger} \]

\[ 29.36 \times \$3.74 = \$109.80 \]

Since Kroger's current share price is $33.59, this is quite a ways off. Generally you will want to use quite a few comparables and take an average of the result. Also, you want to do your best to pick truly comparable companies. I.e…. is Amazon comparable/like/similar?

Despite being extremely error prone, imprecise, and assuming efficient markets, comparables are used excessively by the following:

1. Investment Bankers pricing a private firm to go public in an IPO.
2. Private Equity analysts determining the value of an investment.
3. Investors/Analysts who do not want to do DCF.
4. Pretty much…everyone. (for better or worse)

My personal opinion—fun to look at, but discount the result heavily (i.e. don't trust it).

Let's suppose you choose your investments after doing your comparables and DCF and financial statement analysis so you know all of what you would like to invest in and whittled down the filter set to 40 or so 'good' companies.

• Individually, each one looks like a fine investment.
• But we are running a portfolio, we need to consider how they fit together.
• Buying one asset that makes money, when another asset loses money, is a terrible idea. (i.e. buying Tesla Motors and Ford Motors together, there are limited arguments to this as a successful bet.)
• Puglia notes, good firms are firms which have growing market share in a growing market. Market share is capped at 100%, firms compete. Buying a firm which is growing in market share necessarily means not buying the one(s) that is (are) shrinking.

First, plot your possible investments together.

• We do this not by using their prices, but by constructing wealth indexes. Wealth index is no more than how much 1 dollar would grow if we had invested it into that stock.
• This makes sure that the price of the company is not considered in making the investment, but rather its compounded return!

\[ wealth_t = \$1 \prod_{t=1}^T (1+r_t) \]

\( \prod_{t=1}^T (1+r_t) = (1+r_1)(1+r_2)(1+r_3)\dots(1+r_T) \)

1. Go collect their prices from Yahoo, Bloomberg, Reuters, etc.
2. Compute their returns:
   • \( r_t = \frac{P_1-P_0}{P_0} = \frac{P_1}{P_0}-1 \)
   • \( r_t = ln(\frac{P_1}{P_0}) \) (short-term freq only.)
3. Compute wealth index (1 times daily return plus 1 and compound up each day.)

After plotting them you may notice that some of your 'great picks' under-perform:

1. Check their volume, they may not have enough liquidity.

2. They may not be well known.

   • This could mean you could get in early.
   • Or, that you have missed an important detail and they have a redundant product.

3. Make the selection of firms you want to include. Be sure not to overweight one sector.

Next, naturally you want to be choosing investments which work well together in a portfolio. Having just chosen 'good' investments that have either strong value or growth prospects you can move to the optimization stage.

This will attempt to do the following:

1. Improve return of the portfolio (maximize return)
2. Reduce the risk of the portfolio (minimize risk)
3. Knock out what are known as 'sub-dominated' assets (i.e. those which are not worth it from a risk-return perspective).

Portfolio optimization is also a selection tool. A phenomenal stock that ruins a portfolio's risk prospects should never be included.

Portfolio optimization is simply a way to select the highest return subject to risk that you can achieve given all the possible weights of assets in your portfolio.

The portfolio with the highest return to risk ratio will have the highest Sharpe:

\[ Sharpe\ Ratio = \frac{E(r_p)-r_f}{\sigma_p} \approx \frac{Excess\ Return}{Risk} \]

So the 'Tangency portfolio' is the one with the highest Sharpe and is also optimal.

If markets are efficient, the tangency portfolio is also the market portfolio.

This is why the case mentions passive and active investors.

1. If you go through the selection process, and markets are efficient—then you are better off simply holding the market portfolio.

   • No need to do all this analysis. If markets are efficient, your result will come up with the same investments as those already in the market portfolio. In which case, invest in a market index to begin with and move on (a la Warren Buffett's suggestion). (Passive Investing)

2. If markets are not efficient, then you may be able to out-perform, by making superior selections and having a better portfolio. (Active Investing)

Assuming you fall on the side of Puglia and not Buffett – and you want any sort of job in finance – you have to be willing to accept that markets are not forever and always efficient.

1. Temporary Mispricings – Temporary mispricings are caused by volatility. You experienced this during the crash of 2020. Prices dropped, people sold (also behavioral) on rational expectations that were unfounded. Prices rebound. Buying the dip earned a mint.
2. Behavioral Mispricings – People are emotional, not always rational. Groups are worse. (GameStop, Dotcom bubble, Storming the Capital…etc.)
3. Information Break-downs/Inefficiency – Information is not as free-flowing as we think. Some have more than others.

Assuming you agree that markets are not always efficient, or you are naive enough to hope to beat the market. You plan to optimize your selection. Yes, we could use a lot of math…

\[ \min_{w_1,w_2,\dots,w_n} \boldsymbol{w}\boldsymbol{\varOmega}\boldsymbol{w'} \]

\[ s.t.\ \ \boldsymbol{r'}\boldsymbol{w} \]

\[ \sigma^2_{p_5}= \boldsymbol{w}\boldsymbol{\varOmega}\boldsymbol{w'} = \begin{bmatrix} w_1 & w_2 & w_3 & w_4 & w_5 \end{bmatrix} \begin{bmatrix} \sigma^2_1 & \sigma_{1,2} & \sigma_{1,3} & \sigma_{1,4} & \sigma_{1,5} \\ \sigma_{2,1} & \sigma^2_2& \sigma_{2,3} & \sigma_{2,4} & \sigma_{2,5} \\ \sigma_{3,1} & \sigma_{3,2} & \sigma^2_3 & \sigma_{3,4} & \sigma_{3,5} \\ \sigma_{4,1} & \sigma_{4,2} & \sigma_{4,3} &\sigma^2_4 & \sigma_{4,5} \\ \sigma_{5,1} & \sigma_{5,2} & \sigma_{5,3} & \sigma_{5,4} & \sigma^2_5 \\ \end{bmatrix} \begin{bmatrix} w_1 \\ w_2 \\ w_3 \\ w_4 \\ w_5 \end{bmatrix} \]

After you set up your portfolio which may or may not out perform the market already. Perhaps go a step further and learn to hedge with derivatives.

1.When the macro-economics indicate the market will drop.